MINF4533: Networks and Business Intelligence Prof. Dr. Daning Hu Department of Informatics University of Zurich Sep 18th, 2012

2 Daning Hu: A Network Perspective Daning Hu studied at advises works at advises collaborates Dr. J. Leon Zhao Jiaqi Yan John collaborates Social Network Analysis Financial Intelligence Jiaqi Jackie Yan, 29, Male, Chinese ?

3 MINF 4533: Networks and Business Intelligence Lecturer: Prof. Dr. Daning Hu Teaching Assistant: Dr. Jiaqi Yan (In all s to me, please put MINF 4533 in the subject line. This can me get to you Credits: 4.5 ECTS credits Class Meetings: Tuesday 13:30-15:00 PM Tutorials: Thursday 10:00 – 11:30 AM Language: English Audience: Undergraduate and Master students Office Hours: 15:00 -16:00, for appointment, Room 2.A.12

4 Course Plan This lecture mainly consists of two stages.  to 18.10: the lecturer will introduce the basics of network modeling and analysis techniques. The students will also gain hands on experiences in tutorials to 08.11: the students will work and finish the midterm project.  to 06.12: the lecturer will introduce the various business intelligence applications based on network modeling and analysis to : the students will work and finish the final project.

5 Grading and Course Goals 1. Two course projects. One midterm and one final project (each taking 40%, total is 80%) 2. Active participation and interaction during the lectures and tutorials (20%) The project reports should include the following four major components:  Network/Relational Data Collection (7.5%)  Network Data Processing and Modeling (10%)  Network Visualization (7.5%)  Network Analysis (15%)

6 Example 1: Network Data Collection Social Networks: Online communities, Social networking websites, Personal blogs and micro-bloggings, online video sharing websites. E-Business: Amazon Web Service, Ebay Data API, Taobao. Others: Financial, Governmental data sources, etc.

7 Example 2: Network Data Processing Modeling Extract relations/links from raw data in database tables Model such relations/links into network data.  Node data  Link data

8 Example 3: Network Visualization

9 Example 4: Network Analysis A microblogging Network: Who possesses the most advantageous position in broking information and knowledge in this network?

10 A Global Terrorist Network How to effectively break down terrorist networks?

11 Network-based Business Intelligence Applications Recommendation Systems:

12 Network-based Business Intelligence Applications Reputation Systems:

13 Network-based Business Intelligence Applications Social Media based Marketing, Word-of-Mouth Effect

14 Computing tools required for this course Database Management Software  MySQL or other common DBMS such as MS SQL Server, Oracle, etc. Network Visualization Tool: NetDraw, FNA (Financial Network Analyzer), etc. Network Analysis Tool: UCINet, FNA Microsoft Windows OS Only